so social nets as graphs can see aggregates and individuals as properties of
the set of edges and verticies - so that lets us unify this model - provided we
capture sufficiently rich types of edges (kinship relationships, types of
friendships, encounters, co-membership of clubs, geo-spatial relations,
psycological, etc etc)

it also mighr help explain the dicomty in economics/history where most the
time, most effects are caused by large group behaviour (a la marxist analysis)
but from time to time, indivuduals wirled great influence and impact outcomes
(classical) - so this is just when someone is a hub at a time when opinions are
"hypercritical" ?-- balanced between one extreme and another -- when that
person can sway a large number around them because of their centrality and
degree....

hmm... .. ..

fits with the whole peer-progressive thing too

so this is where small data (and anecdotes and narratives) meet big data

and its also why the butterfly's wingflap causing a hurricane could be something we'd eventually model properly (after all, a trillion butterfly wingflaps happen every year without hurricanes, so its a matter of modeling the right butterfly, or the right Genghis Kahn).